MU-MIMO Interference Cancellation via Permutation Matrix Decomposition
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Solution Overview
Problem
Current multi-user MIMO systems face challenges in achieving low complexity and high performance due to the high complexity of existing algorithms like sphere encoding and transmission VBLAST, which hinder efficient interference cancellation.
Innovation Solution
A method is introduced that involves decomposing the channel matrix into permutation matrices, determining an optimal permutation matrix by calculating the norm of multiplication with the data vector, and using this matrix to calculate a precoding vector, thereby minimizing transmission power and complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If non-linear MU-MIMO algorithms (sphere encoding, transmission VBLAST) are used to improve performance, then interference cancellation capability is enhanced, but system complexity becomes too high to be materialized
Solution Approach 1:
The patent segments the channel matrix decomposition into permutation matrices and triangular matrices, allowing the complex interference cancellation problem to be broken down into manageable steps. The channel matrix H is decomposed as H = P1*P2*...*Pm*U, where each component has specific properties that simplify the overall computation while maintaining interference cancellation capability.
Solution Approach 2:
The patent changes the approach by using permutation matrices with specific structural properties (unitary matrices with one entry per row/column equal to 1) to transform the channel matrix. This parameter change from general matrix decomposition to permutation-based decomposition reduces computational complexity while preserving the interference cancellation performance.
2Reliability
If full CSIT MU-MIMO is implemented to achieve better performance, then signal quality is improved, but feedback requirements increase significantly
Solution Approach 1:
The patent extracts the essential information needed for interference cancellation from the full channel state information. By using permutation matrices that can be determined with reduced feedback, the system achieves sufficient performance without requiring complete CSIT feedback, thus reducing the feedback quantity while maintaining signal quality.
Data Source
AI summary
The present invention relates to a transmission interference cancellation method for a multiuser MIMO system. The method includes decomposing a channel matrix to represent formulae of permutation matrixes including a first matrix and a second matrix; determining an optimal permutation matrix among a plurality of available permutation matrixes using a norm of multiplication of the second matrix and a transmitting data vector; and determining the second matrix using the determined optimal permutation matrix and calculating a transmitting precoding vector using the determined second matrix and the transmitting data vector.